{"id":"W4294636412","doi":"10.5267/j.uscm.2022.7.011","title":"A structural equation model for analyzing the relationship between enterprise resource planning and digital supply chain management","year":2022,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"ERP Systems Implementation and Impact","field":"Business, Management and Accounting","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digitization; Structural equation modeling; Enterprise resource planning; Business; Supply chain; Supply chain management; Process management; Resource (disambiguation); Process (computing); Knowledge management; Industrial organization; Order (exchange); Digital firm; Operations management; Marketing; Computer science; Enterprise information system; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005532761,0.001422522,0.001204298,0.002915046,0.001263302,0.001765982,0.002319732,0.002021997,0.01223783],"category_scores_gemma":[0.01502748,0.001078089,0.00170856,0.004531859,0.0007361436,0.002718617,0.002017083,0.003356507,0.001325947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00284009,"about_ca_system_score_gemma":0.005568153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01860368,"about_ca_topic_score_gemma":0.01764783,"domain_scores_codex":[0.9962168,0.0026311,0.0001872583,0.0002906604,0.000399225,0.0002748167],"domain_scores_gemma":[0.9915608,0.006715934,0.0006035616,0.000176365,0.0007284153,0.0002150233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001145793,0.004124949,0.3241827,0.001183006,0.003033955,0.002047352,0.01147011,0.2381207,0.00286411,0.2714518,0.01643637,0.1239391],"study_design_scores_gemma":[0.0005977019,0.001805596,0.0365948,0.0005621338,0.0007442494,0.0004605799,0.004706608,0.8798056,0.0005175699,0.05979881,0.01426105,0.0001452484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5787243,0.0008754996,0.3785038,0.005264839,0.000495965,0.003250937,0.008690497,0.0008353812,0.02335874],"genre_scores_gemma":[0.8503765,0.0007586806,0.1307258,0.0003196281,0.00009667755,0.005896016,0.004609987,0.00005921752,0.007157463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01860368,"threshold_uncertainty_score":0.04093957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0661070392724093,"score_gpt":0.2969548426356756,"score_spread":0.2308478033632663,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}